NVIDIA
Explore
Models
Blueprints
GPUs
Docs
⌘KCtrl+K
Terms of Use
Privacy Policy
Your Privacy Choices
Contact

Copyright © 2026 NVIDIA Corporation

Models

Deploy and scale models on your GPU infrastructure of choice with NVIDIA NIM inference microservices

Optimized by NVIDIALaunch from Hugging FaceBeta

Filters (1)

  • Free Endpoint
    2
  • Partner Endpoint
    1
  • Download Available
    5
  • Retrieval Augmented Generation
    7
  • Text-to-Embedding
    6
  • Drug Discovery
    0
  • Image-to-Text
    0
  • Code Generation
    0
  • Deep Infra
    1
  • Together AI
    0
  • GMI Cloud
    0
  • Bitdeer AI
    0
  • CoreWeave
    0
  • NVIDIA
    7
  • Meta
    0
  • Mistral AI
    0
  • Qwen
    0
  • Google
    0
  • A100 SXM4 80GB
    0
  • B200
    0
  • GB200
    0
  • GH200 144G HBM3e
    0
  • H100 80GB HBM3
    0
  • nemo retriever
    • 7 models
    NVIDIA
    Downloadable

    llama-nemotron-embed-1b-v2

    Multilingual, cross-lingual embedding model for long-document QA retrieval, supporting 26 languages.
    Text-to-Embedding
    2mo
    Items per page
    of 1 pages
    28.38M
    NVIDIA
    Downloadable

    llama-nemotron-embed-vl-1b-v2

    Multimodal question-answer retrieval representing user queries as text and documents as images.
    nemo retriever
    6.65M
    2mo
    NVIDIA
    Downloadable

    llama-3_2-nemoretriever-300m-embed-v2

    Multilingual, cross-lingual embedding model for long-document QA retrieval, supporting 26 languages.
    Text-to-Embedding
    94
    7mo
    NVIDIA
    Free Endpoint

    llama-3_2-nemoretriever-300m-embed-v1

    Multilingual, cross-lingual embedding model for long-document QA retrieval, supporting 26 languages.
    Text-to-Embedding
    464K
    9mo
    NVIDIA
    Free Endpoint

    nv-embedcode-7b-v1

    The NV-EmbedCode model is a 7B Mistral-based embedding model optimized for code retrieval, supporting text, code, and hybrid queries.
    nemo retriever
    125K
    11mo
    NVIDIA
    Downloadable

    llama-3.2-nv-embedqa-1b-v2

    Multilingual and cross-lingual text question-answering retrieval with long context support and optimized data storage efficiency.
    nemo retriever
    2.41M
    9mo
    NVIDIA
    Downloadable

    nv-embedqa-e5-v5

    English text embedding model for question-answering retrieval.
    Embedding
    16.61M
    9mo